Author: Doris Dimitriadis/Dimitriadou, Denisa R. Goia, M. Saiful Huq, Ronald John Lalonde, Noor Mail, Adam Olson, Tyler Wilhite 👨🔬
Affiliation: UPMC Hillman Cancer Center, UPMC Hillman Cancer Center and University of Pittsburgh School of Medicine, UPMC 🌍
Purpose: The goal of the HyperSight® offline adaptive-workflow is to create a methodical approach to adaptive-radiotherapy (ART) that considers modifications in patient setup and anatomy. Through efficient teamwork and cutting-edge technologies, the objectives are to guarantee accurate dose delivery, preserve target coverage, reduce normal-tissue exposure, and improve treatment quality.
Methods: Physicians are notified in ARIA to submit requests for re-simulation and adaptive-planning timelines as part of the workflow. Auto-contouring is aided by LIMBUS AI® to expedite the procedure. Re-optimization is performed using Hypersight® iCBCT-ACUROS (iterative-Cone-Beam-Computed-Tomography) images, which ensure a sufficient field-of-view (FOV) to capture body contours, targets, and organs at risk (OARs). Treatment plans are modified in accordance with the revised dose constraints, which are based on the delivered dose and remaining fractions. Co-registration checks, quality assurance (QA) techniques such as monitor unit checks and IMRT QA, and cumulative-dose evaluations using a plan sum are all examples of validation. Every adaptation, including the justification for any deviations, is fully documented. Continuous-workflow improvements are ensured by routinely reporting results and comments from clinical experiences.
Results: The process guarantees effective adaptation within a 48-hour window while considering urgent situations that call for faster turnaround times. The incorporation of sophisticated tools, like HyperSight® advanced imaging algorithms and LIMBUS AI® automated contouring, enables precise contouring and dose adjustments. Errors are reduced and patient care is optimized when team communication and documentation are consistent. Better dose conformance to targets, OAR sparing, and accelerated-adaptive-processes are achieved by using the images acquired at the treatment console.
Conclusion: A strong foundation for ART can be provided by the Hypersight offline adaptive workflow, which strikes a balance between accuracy and efficiency while accommodating patient-specific changes. Ongoing quality improvement, leveraging feedback and technological advancements, ensures the workflow remains responsive to evolving clinical demands, ultimately enhancing treatment safety and efficacy.